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Journal of Food Measurement and Characterization

, Volume 11, Issue 4, pp 2142–2150 | Cite as

Computer vision coupled with laser backscattering for non-destructive colour evaluation of papaya during drying

  • Patchimaporn UdomkunEmail author
  • Marcus Nagle
  • Dimitrios Argyropoulos
  • Alexander Nimo Wiredu
  • Busarakorn Mahayothee
  • Joachim Müller
Original Paper

Abstract

Colour change is a common physical phenomenon observed during drying, which need to be controlled since it directly affects consumer acceptance of dried products. This study aimed to investigate the feasibility of using computer vision, combined with laser light backscattering analysis at 650 nm in order to predict colour changes of papaya during drying. The results revealed that each image-processing factor obtained can potentially be used to describe every colour attribute change, except for chroma value. The multivariate correlations of measured backscattering parameters as well as the digital image properties were found to yield the best fitting for colour validations. Interestingly, the use of computer vision technique coupled with laser backscattering methods provides a reliable tool for quality control based on a rapid, consistent, and non-intrusive method for in-line quality measurement in established fruit drying processes.

Keywords

Colour change Laser backscattering Computer vision system Quality control Drying Papaya 

List of symbols

0

Initial value

ΔE

Total colour difference

a*

Intensity in green-red

AI

Illuminated area (pixel)

b*

Intensity in blue-yellow

C*

Chroma

CA

Colour attribute

CAcvs

Colour image of papaya

CAexp

Experimentally observed colour attribute

CApre

Predicted colour attribute

CR-100

Chroma meter

CVS

Computer vision systems

f(x)

Converted value sR, sG, or sB

h*

Hue (°)

IL

Light intensity

L*

Lightness

MAPE

Mean absolute percentage error (%)

N

Number of observations

PPO

Polyphenoloxidase

RGB

Red, green, and blue

RH

Relative humidity (%)

R2

Coefficients of determination

sR, sG, sB

Components of sRGB

t

Time

x

Value of R′, G′, or B′

yimage

Image attribute

Xn, Yn, Zn

XYZ values of a reference white colour

Notes

Acknowledgements

This research was the result of a scholarship from the Food Security Center of Universität Hohenheim, which is part of the DAAD (German Academic Exchange Service) Program “Exceed”. It was also supported by DAAD and the German Federal Ministry for Economic Cooperation and Development (BMZ). This research was also undertaken as part of the CGIAR Research Program on Agriculture for Nutrition and Health, and supported by International Institute of Tropical Agriculture (IITA). The authors gratefully acknowledge the International Fund for Agricultural Development (IFAD) and the European Commission (EC) (PJ-002057) for giving the opportunity to prepare this article. The authors also acknowledge the contributions of the “Feed the future Mozambique improved seeds for better agriculture (SEMEAR)” which supported co-authorships of the paper. We gratefully acknowledge the financial support. We are also grateful to Mrs. Ingrid Amberg and Mrs. Dorothea Hirschbach-Müller for their technical support.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Patchimaporn Udomkun
    • 1
    Email author
  • Marcus Nagle
    • 2
  • Dimitrios Argyropoulos
    • 2
  • Alexander Nimo Wiredu
    • 3
  • Busarakorn Mahayothee
    • 4
  • Joachim Müller
    • 2
  1. 1.International Institute of Tropical Agriculture (IITA)BukavuDemocratic Republic of the Congo
  2. 2.Institute of Agricultural Engineering, Tropics and Subtropics GroupUniversität HohenheimStuttgartGermany
  3. 3.International Institute of Tropical Agriculture (IITA)NampulaMozambique
  4. 4.Department of Food TechnologySilpakorn UniversityNakhon PathomThailand

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